Objective: This study aimed to investigate which characteristics of athlete, wheelchair and athlete-wheelchair interface are the best predictors of wheelchair basketball mobility performance. Design: A total of 60 experienced wheelchair basketball players performed a wheelchair mobility performance test to assess their mobility performance. To determine which variables were the best predictors of mobility performance, forward stepwise linear regression analyses were performed on a set of 33 characteristics, including 10 athlete, 19 wheelchair, and 4 athlete-wheelchair interface characteristics. Results: A total of 8 of the characteristics turned out to be significant predictors of wheelchair basketball mobility performance. Classification, experience, maximal isometric force, wheel axis height, and hand rim diameter—which both are interchangeable with each other and wheel diameter—camber angle, and the vertical distance between shoulder and rear wheel axis—which was interchangeable with seat height—were positively associated with mobility performance. The vertical distance between the front seat and the footrest was negatively associated with mobility performance. Conclusion: With this insight, coaches and biomechanical specialists are provided with statistical findings to determine which characteristics they could focus on best to improve mobility performance. Six out of 8 predictors are modifiable and can be optimized to improve mobility performance. These adjustments could be carried out both in training (maximal isometric force) and in wheelchair configurations (eg, camber angle). https://doi.org/10.1123/jsr.2017-0142 LinkedIn: https://www.linkedin.com/in/annemarie-de-witte-9582b154/ https://www.linkedin.com/in/moniqueberger/ https://www.linkedin.com/in/rienkvdslikke/
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In wheelchair sports, the use of Inertial Measurement Units (IMUs) has proven to be one of the most accessible ways for ambulatory measurement of wheelchair kinematics. A three-IMU configuration, with one IMU attached to the wheelchair frame and two IMUs on each wheel axle, has previously shown accurate results and is considered optimal for accuracy. Configurations with fewer sensors reduce costs and could enhance usability, but may be less accurate. The aim of this study was to quantify the decline in accuracy for measuring wheelchair kinematics with a stepwise sensor reduction. Ten differently skilled participants performed a series of wheelchair sport specific tests while their performance was simultaneously measured with IMUs and an optical motion capture system which served as reference. Subsequently, both a one-IMU and a two-IMU configuration were validated and the accuracy of the two approaches was compared for linear and angular wheelchair velocity. Results revealed that the one-IMU approach show a mean absolute error (MAE) of 0.10 m/s for absolute linear velocity and a MAE of 8.1◦/s for wheelchair angular velocity when compared with the reference system. The twoIMU approach showed similar differences for absolute linear wheelchair velocity (MAE 0.10 m/s), and smaller differences for angular velocity (MAE 3.0◦/s). Overall, a lower number of IMUs used in the configuration resulted in a lower accuracy of wheelchair kinematics. Based on the results of this study, choices regarding the number of IMUs can be made depending on the aim, required accuracy and resources available.
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Athlete impairment level is an important factor in wheelchair mobility performance (WMP) in sports. Classification systems, aimed to compensate impairment level effects on performance, vary between sports. Improved understanding of resemblances and differences in WMP between sports could aid in optimizing the classification methodology. Furthermore, increased performance insight could be applied in training and wheelchair optimization. The wearable sensor-based wheelchair mobility performance monitor (WMPM) was used to measure WMP of wheelchair basketball, rugby and tennis athletes of (inter-)national level during match-play. As hypothesized, wheelchair basketball athletes show the highest average WMP levels and wheelchair rugby the lowest, whereas wheelchair tennis athletes range in between for most outcomes. Based on WMP profiles, wheelchair basketball requires the highest performance intensity, whereas in wheelchair tennis, maneuverability is the key performance factor. In wheelchair rugby, WMP levels show the highest variation comparable to the high variation in athletes’ impairment levels. These insights could be used to direct classification and training guidelines, with more emphasis on intensity for wheelchair basketball, focus on maneuverability for wheelchair tennis and impairment-level based training programs for wheelchair rugby. Wearable technology use seems a prerequisite for further development of wheelchair sports, on the sports level (classification) and on individual level (training and wheelchair configuration).
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